Rule-Based Method for Morphological Classification of ST Segment in ECG Signals
- 25 November 2015
- journal article
- Published by Springer Science and Business Media LLC in Journal of Medical and Biological Engineering
- Vol. 35 (6), 816-823
- https://doi.org/10.1007/s40846-015-0092-x
Abstract
No abstract availableKeywords
This publication has 13 references indexed in Scilit:
- A multi-step method with signal quality assessment and fine-tuning procedure to locate maternal and fetal QRS complexes from abdominal ECG recordingsPhysiological Measurement, 2014
- ECG quality assessment based on a kernel support vector machine and genetic algorithm with a feature matrixJournal of Zhejiang University SCIENCE C, 2014
- ST shape classification in ECG by constructing reference ST setMedical Engineering & Physics, 2010
- Real-time detection of transient cardiac ischemic episodes from ECG signalsPhysiological Measurement, 2009
- An Algorithm for Robust and Efficient Location of T-Wave Ends in ElectrocardiogramsIEEE Transactions on Biomedical Engineering, 2006
- An association rule mining-based methodology for automated detection of ischemic ECG beatsIEEE Transactions on Biomedical Engineering, 2006
- EVALUATION OF CLASSIFIERS FOR AN UNEVEN CLASS DISTRIBUTION PROBLEMApplied Artificial Intelligence, 2006
- Automatic Classification of Heartbeats Using ECG Morphology and Heartbeat Interval FeaturesIEEE Transactions on Biomedical Engineering, 2004
- Automated detection of transient ST-segment episodes in 24h electrocardiogramsMedical & Biological Engineering & Computing, 2004
- ST-segment monitoring with continuous 12-lead ECG improves early risk stratification in patients with chest pain and ECG nondiagnostic of acute myocardial infarctionJournal of the American College of Cardiology, 1999